Zobrazeno 1 - 10
of 57
pro vyhledávání: '"Latorre, Vittorio"'
Public transportation plays a crucial role in our lives, and the road network is a vital component in the implementation of smart cities. Recent advancements in AI have enabled the development of advanced monitoring systems capable of detecting anoma
Externí odkaz:
http://arxiv.org/abs/2407.15406
Autor:
Latorre, Vittorio
This paper presents an efficient 51 lines Matlab code to solve topology optimization problems. By the fact that the presented code is based on an hard 0-1 optimization method that handles the integer part of the optimization in a simple fashion and i
Externí odkaz:
http://arxiv.org/abs/1902.00877
Autor:
Latorre, Vittorio, Gao, David Yang
This paper presents a new canonical duality methodology for solving general nonlinear dynamical systems. Instead of the conventional iterative methods, the discretized nonlinear system is first formulated as a global optimization problem via the leas
Externí odkaz:
http://arxiv.org/abs/1512.08343
Canonical duality-triality is a breakthrough methodological theory, which can be used not only for modeling complex systems within a unified framework, but also for solving a wide class of challenging problems from real-world applications. This paper
Externí odkaz:
http://arxiv.org/abs/1410.2665
Autor:
Latorre, Vittorio
We propose to solve large instances of the non-convex optimization problems reformulated with canonical duality theory. To this aim we propose an interior point potential reduction algorithm based on the solution of the primal-dual total complementar
Externí odkaz:
http://arxiv.org/abs/1403.5991
This paper presents an application of Canonical duality theory to the solution of contact problems with Coulomb friction. The contact problem is formulated as a quasi-variational inequality which solution is found by solving its Karush-Kunt-Tucker sy
Externí odkaz:
http://arxiv.org/abs/1402.6909
Autor:
Latorre, Vittorio, Gao, David Y.
This paper presents a canonical duality theory for solving a general nonconvex constrained optimization problem within a unified framework to cover Lagrange multiplier method and KKT theory. It is proved that if both target function and constraints p
Externí odkaz:
http://arxiv.org/abs/1310.2014
Autor:
Latorre, Vittorio, Gao, David Yang
Radial Basis Functions Neural Networks (RBFNNs) are tools widely used in regression problems. One of their principal drawbacks is that the formulation corresponding to the training with the supervision of both the centers and the weights is a highly
Externí odkaz:
http://arxiv.org/abs/1302.4141
Autor:
Georgoulis Manolis K., Bloomfield D. Shaun, Piana Michele, Massone Anna Maria, Soldati Marco, Gallagher Peter T., Pariat Etienne, Vilmer Nicole, Buchlin Eric, Baudin Frederic, Csillaghy Andre, Sathiapal Hanna, Jackson David R., Alingery Pablo, Benvenuto Federico, Campi Cristina, Florios Konstantinos, Gontikakis Constantinos, Guennou Chloe, Guerra Jordan A., Kontogiannis Ioannis, Latorre Vittorio, Murray Sophie A., Park Sung-Hong, von Stachelski Samuel, Torbica Aleksandar, Vischi Dario, Worsfold Mark
Publikováno v:
Journal of Space Weather and Space Climate, Vol 11, p 39 (2021)
The European Union funded the FLARECAST project, that ran from January 2015 until February 2018. FLARECAST had a research-to-operations (R2O) focus, and accordingly introduced several innovations into the discipline of solar flare forecasting. FLAREC
Externí odkaz:
https://doaj.org/article/30ac247768104f16acced7f8204b51fc
